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            <article class="content wrap" id="_content" data-uid="Keras.Layers.Conv2D">
  
  
  <h1 id="Keras_Layers_Conv2D" data-uid="Keras.Layers.Conv2D" class="text-break">Class Conv2D
  </h1>
  <div class="markdown level0 summary"><p>2D convolution layer (e.g. spatial convolution over images).
This layer creates a convolution kernel that is convolved with the layer input to produce a tensor of outputs.If use_bias is True, a bias vector is created and added to the outputs.Finally, if activation is not None, it is applied to the outputs as well.
When using this layer as the first layer in a model, provide the keyword argument input_shape (tuple of integers, does not include the batch axis), e.g. input_shape=(128, 128, 3) for 128x128 RGB pictures in data_format=&quot;channels_last&quot;.</p>
</div>
  <div class="markdown level0 conceptual"></div>
  <div class="inheritance">
    <h5>Inheritance</h5>
    <div class="level0"><span class="xref">System.Object</span></div>
    <div class="level1"><a class="xref" href="Keras.Keras.html">Keras</a></div>
    <div class="level2"><a class="xref" href="Keras.Base.html">Base</a></div>
    <div class="level3"><a class="xref" href="Keras.Layers.BaseLayer.html">BaseLayer</a></div>
    <div class="level4"><span class="xref">Conv2D</span></div>
  </div>
  <div classs="implements">
    <h5>Implements</h5>
    <div><span class="xref">System.IDisposable</span></div>
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  <div class="inheritedMembers">
    <h5>Inherited Members</h5>
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      <a class="xref" href="Keras.Layers.BaseLayer.html#Keras_Layers_BaseLayer_Set_Keras_Layers_BaseLayer___">BaseLayer.Set(BaseLayer[])</a>
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      <a class="xref" href="Keras.Base.html#Keras_Base_Parameters">Base.Parameters</a>
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      <a class="xref" href="Keras.Base.html#Keras_Base_Init">Base.Init()</a>
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    <div>
      <a class="xref" href="Keras.Base.html#Keras_Base_ToPython">Base.ToPython()</a>
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    <div>
      <a class="xref" href="Keras.Base.html#Keras_Base_InvokeStaticMethod_System_Object_System_String_System_Collections_Generic_Dictionary_System_String_System_Object__">Base.InvokeStaticMethod(Object, String, Dictionary&lt;String, Object&gt;)</a>
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      <a class="xref" href="Keras.Base.html#Keras_Base_InvokeMethod_System_String_System_Collections_Generic_Dictionary_System_String_System_Object__">Base.InvokeMethod(String, Dictionary&lt;String, Object&gt;)</a>
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      <a class="xref" href="Keras.Base.html#Keras_Base_Item_System_String_">Base.Item[String]</a>
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      <a class="xref" href="Keras.Keras.html#Keras_Keras_Instance">Keras.Instance</a>
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      <a class="xref" href="Keras.Keras.html#Keras_Keras_keras2onnx">Keras.keras2onnx</a>
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      <a class="xref" href="Keras.Keras.html#Keras_Keras_Dispose">Keras.Dispose()</a>
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      <a class="xref" href="Keras.Keras.html#Keras_Keras_ToTuple_System_Array_">Keras.ToTuple(Array)</a>
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      <a class="xref" href="Keras.Keras.html#Keras_Keras_ToList_System_Array_">Keras.ToList(Array)</a>
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    <div>
      <span class="xref">System.Object.Equals(System.Object)</span>
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      <span class="xref">System.Object.Equals(System.Object, System.Object)</span>
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      <span class="xref">System.Object.GetHashCode()</span>
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      <span class="xref">System.Object.GetType()</span>
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      <span class="xref">System.Object.MemberwiseClone()</span>
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      <span class="xref">System.Object.ReferenceEquals(System.Object, System.Object)</span>
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      <span class="xref">System.Object.ToString()</span>
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  </div>
  <h6><strong>Namespace</strong>: <a class="xref" href="Keras.Layers.html">Keras.Layers</a></h6>
  <h6><strong>Assembly</strong>: Keras.dll</h6>
  <h5 id="Keras_Layers_Conv2D_syntax">Syntax</h5>
  <div class="codewrapper">
    <pre><code class="lang-csharp hljs">public class Conv2D : BaseLayer, IDisposable</code></pre>
  </div>
  <h3 id="constructors">Constructors
  </h3>
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    <a href="https://github.com/SciSharp/Keras.NET/new/master/apiSpec/new?filename=Keras_Layers_Conv2D__ctor_System_Int32_System_Tuple_System_Int32_System_Int32__System_Tuple_System_Int32_System_Int32__System_String_System_String_System_Tuple_System_Int32_System_Int32__System_String_System_Boolean_System_String_System_String_System_String_System_String_System_String_System_String_System_String_Keras_Shape_.md&amp;value=---%0Auid%3A%20Keras.Layers.Conv2D.%23ctor(System.Int32%2CSystem.Tuple%7BSystem.Int32%2CSystem.Int32%7D%2CSystem.Tuple%7BSystem.Int32%2CSystem.Int32%7D%2CSystem.String%2CSystem.String%2CSystem.Tuple%7BSystem.Int32%2CSystem.Int32%7D%2CSystem.String%2CSystem.Boolean%2CSystem.String%2CSystem.String%2CSystem.String%2CSystem.String%2CSystem.String%2CSystem.String%2CSystem.String%2CKeras.Shape)%0Asummary%3A%20'*You%20can%20override%20summary%20for%20the%20API%20here%20using%20*MARKDOWN*%20syntax'%0A---%0A%0A*Please%20type%20below%20more%20information%20about%20this%20API%3A*%0A%0A">Improve this Doc</a>
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    <a href="https://github.com/SciSharp/Keras.NET/blob/master/Keras/Layers/Convolution.cs/#L85">View Source</a>
  </span>
  <a id="Keras_Layers_Conv2D__ctor_" data-uid="Keras.Layers.Conv2D.#ctor*"></a>
  <h4 id="Keras_Layers_Conv2D__ctor_System_Int32_System_Tuple_System_Int32_System_Int32__System_Tuple_System_Int32_System_Int32__System_String_System_String_System_Tuple_System_Int32_System_Int32__System_String_System_Boolean_System_String_System_String_System_String_System_String_System_String_System_String_System_String_Keras_Shape_" data-uid="Keras.Layers.Conv2D.#ctor(System.Int32,System.Tuple{System.Int32,System.Int32},System.Tuple{System.Int32,System.Int32},System.String,System.String,System.Tuple{System.Int32,System.Int32},System.String,System.Boolean,System.String,System.String,System.String,System.String,System.String,System.String,System.String,Keras.Shape)">Conv2D(Int32, Tuple&lt;Int32, Int32&gt;, Tuple&lt;Int32, Int32&gt;, String, String, Tuple&lt;Int32, Int32&gt;, String, Boolean, String, String, String, String, String, String, String, Shape)</h4>
  <div class="markdown level1 summary"><p>Initializes a new instance of the <a class="xref" href="Keras.Layers.Conv2D.html">Conv2D</a> class.</p>
</div>
  <div class="markdown level1 conceptual"></div>
  <h5 class="decalaration">Declaration</h5>
  <div class="codewrapper">
    <pre><code class="lang-csharp hljs">public Conv2D(int filters, Tuple&lt;int, int&gt; kernel_size, Tuple&lt;int, int&gt; strides = null, string padding = &quot;valid&quot;, string data_format = &quot;channels_last&quot;, Tuple&lt;int, int&gt; dilation_rate = null, string activation = &quot;&quot;, bool use_bias = true, string kernel_initializer = &quot;glorot_uniform&quot;, string bias_initializer = &quot;zeros&quot;, string kernel_regularizer = &quot;&quot;, string bias_regularizer = &quot;&quot;, string activity_regularizer = &quot;&quot;, string kernel_constraint = &quot;&quot;, string bias_constraint = &quot;&quot;, Shape input_shape = null)</code></pre>
  </div>
  <h5 class="parameters">Parameters</h5>
  <table class="table table-bordered table-striped table-condensed">
    <thead>
      <tr>
        <th>Type</th>
        <th>Name</th>
        <th>Description</th>
      </tr>
    </thead>
    <tbody>
      <tr>
        <td><span class="xref">System.Int32</span></td>
        <td><span class="parametername">filters</span></td>
        <td><p>Integer, the dimensionality of the output space (i.e. the number of output filters in the convolution).</p>
</td>
      </tr>
      <tr>
        <td><span class="xref">System.Tuple</span>&lt;<span class="xref">System.Int32</span>, <span class="xref">System.Int32</span>&gt;</td>
        <td><span class="parametername">kernel_size</span></td>
        <td><p>An integer or tuple/list of 2 integers, specifying the height and width of the 2D convolution window. Can be a single integer to specify the same value for all spatial dimensions.</p>
</td>
      </tr>
      <tr>
        <td><span class="xref">System.Tuple</span>&lt;<span class="xref">System.Int32</span>, <span class="xref">System.Int32</span>&gt;</td>
        <td><span class="parametername">strides</span></td>
        <td><p>An integer or tuple/list of 2 integers, specifying the strides of the convolution along the height and width. Can be a single integer to specify the same value for all spatial dimensions. Specifying any stride value != 1 is incompatible with specifying any dilation_rate value != 1.</p>
</td>
      </tr>
      <tr>
        <td><span class="xref">System.String</span></td>
        <td><span class="parametername">padding</span></td>
        <td><p>one of &quot;valid&quot; or &quot;same&quot; (case-insensitive). Note that &quot;same&quot; is slightly inconsistent across backends with strides != 1, as described here</p>
</td>
      </tr>
      <tr>
        <td><span class="xref">System.String</span></td>
        <td><span class="parametername">data_format</span></td>
        <td><p>A string, one of &quot;channels_last&quot; or &quot;channels_first&quot;. The ordering of the dimensions in the inputs. &quot;channels_last&quot; corresponds to inputs with shape (batch, height, width, channels) while &quot;channels_first&quot; corresponds to inputs with shape (batch, channels, height, width). It defaults to the image_data_format value found in your Keras config file at ~/.keras/keras.json. If you never set it, then it will be &quot;channels_last&quot;.</p>
</td>
      </tr>
      <tr>
        <td><span class="xref">System.Tuple</span>&lt;<span class="xref">System.Int32</span>, <span class="xref">System.Int32</span>&gt;</td>
        <td><span class="parametername">dilation_rate</span></td>
        <td><p>an integer or tuple/list of 2 integers, specifying the dilation rate to use for dilated convolution. Can be a single integer to specify the same value for all spatial dimensions. Currently, specifying any dilation_rate value != 1 is incompatible with specifying any stride value != 1.</p>
</td>
      </tr>
      <tr>
        <td><span class="xref">System.String</span></td>
        <td><span class="parametername">activation</span></td>
        <td><p>Activation function to use (see activations). If you don't specify anything, no activation is applied (ie. &quot;linear&quot; activation: a(x) = x).</p>
</td>
      </tr>
      <tr>
        <td><span class="xref">System.Boolean</span></td>
        <td><span class="parametername">use_bias</span></td>
        <td><p>Boolean, whether the layer uses a bias vector.</p>
</td>
      </tr>
      <tr>
        <td><span class="xref">System.String</span></td>
        <td><span class="parametername">kernel_initializer</span></td>
        <td><p>Initializer for the kernel weights matrix (see initializers).</p>
</td>
      </tr>
      <tr>
        <td><span class="xref">System.String</span></td>
        <td><span class="parametername">bias_initializer</span></td>
        <td><p>Initializer for the bias vector (see initializers).</p>
</td>
      </tr>
      <tr>
        <td><span class="xref">System.String</span></td>
        <td><span class="parametername">kernel_regularizer</span></td>
        <td><p>Regularizer function applied to the kernel weights matrix (see regularizer).</p>
</td>
      </tr>
      <tr>
        <td><span class="xref">System.String</span></td>
        <td><span class="parametername">bias_regularizer</span></td>
        <td><p>Regularizer function applied to the bias vector (see regularizer).</p>
</td>
      </tr>
      <tr>
        <td><span class="xref">System.String</span></td>
        <td><span class="parametername">activity_regularizer</span></td>
        <td><p>Regularizer function applied to the output of the layer (its &quot;activation&quot;). (see regularizer).</p>
</td>
      </tr>
      <tr>
        <td><span class="xref">System.String</span></td>
        <td><span class="parametername">kernel_constraint</span></td>
        <td><p>Constraint function applied to the kernel matrix (see constraints).</p>
</td>
      </tr>
      <tr>
        <td><span class="xref">System.String</span></td>
        <td><span class="parametername">bias_constraint</span></td>
        <td><p>Constraint function applied to the bias vector (see constraints).</p>
</td>
      </tr>
      <tr>
        <td><a class="xref" href="Keras.Shape.html">Shape</a></td>
        <td><span class="parametername">input_shape</span></td>
        <td><p>4D tensor with shape: (batch, channels, rows, cols) if data_format is &quot;channels_first&quot; or 4D tensor with shape: (batch, rows, cols, channels) if data_format is &quot;channels_last&quot;.</p>
</td>
      </tr>
    </tbody>
  </table>
  <h3 id="implements">Implements</h3>
  <div>
      <span class="xref">System.IDisposable</span>
  </div>
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